In the arena of active trading, a wide range of participants strive to sustain profitability and achieve specific objectives. Whether one is trading equities, futures or currencies, competitors from around the globe implement nearly infinite strategies on a daily basis. One such approach to the marketplace is known as black-box trading.
Black-box trading is a rules-based, fully automated method of engaging the financial markets. The term "black-box" alludes to the proprietary nature of the system or strategy that governs functionality. Black-box trading applications are also referred to as "quant," "automated" or "algorithmic" systems. In addition, they often employ big data analytics and play an integral role in many disciplines including high-frequency trading (HFT).
As technology has evolved, black-box systems have come online to the masses. No longer must one be a large institutional participant to become a practitioner, as individual retail traders also have numerous options readily at their disposal.
How Do Black-Box Trading Systems Work?
The exact specifications of a black-box trading system are typically shrouded in secrecy. Lines of intricate programming code define operations governed by specific trading rules and guidelines. In short, each system is unique, proprietary and protected from public scrutiny.
Every black-box system begins with a trading strategy. The strategy is then translated into computer coding language, integrated into a software trading platform and plugged into the market. However, no matter how intricate the code or robust the platform, a black-box system includes functionality local to three standard areas of trading:
- Signal Generation: In accordance to a concrete set of analytical parameters, the black-box scans a selected market or markets for trading opportunities. Upon the defined criteria being met, a market entry point or "signal" is created. Each signal is a prompt for the automated system to enter a specific market. Signals are based on a vast array of methodologies, with a few of the most common being momentum oscillators, market reversal points or trend following protocols.
- Trade Execution: Upon a signal being created, the black-box automatically places orders at market in accordance with defined parameters. In the event an entry order is executed, the newly opened position is managed by the system's automated framework. Concrete rules govern the location and order type placed upon the market, including stop losses and profit targets. Countless trade management strategies are employed, with a few examples being trailing stops, scalping and scaling.
- Risk Management: Provisions for risk management are regularly included in the makeup of the black-box trading system. Aligning risk to reward on a trade-by-trade or account equity basis is a primary method of controlling levels of market exposure. Portfolio optimisation, position sizing and hedging strategies may then be integrated into trading operations.
It's important to remember that the supreme goal of each black-box system is to create and preserve a quantifiable "edge" in the marketplace. An edge is the means by which a strategy or system consistently gains market share. It may be extremely sophisticated or very simple, depending upon the type of trading and methodology involved in its construction.
The Black-Box Debate: Pros And Cons
Over the last decade, the rise of black-box trading practices has been a hotly debated topic. Pieces of legislation such as the Markets in Financial Instruments Directive (MiFID) in the European Union have formally addressed the role of automation and quant trading in the contemporary marketplace. MiFID II puts forth official guidelines to ensure greater transparency and efficiency surrounding automated trading systems within international markets.
Opponents of black-box trading contend that widespread trade automation serves to undermine the integrity of the financial markets. Essentially, the case against boils down to three main arguments:
- Increased Volatility: The use of automated strategies that instantly place a large number of orders upon the market are capable of spiking periodic volatility. A sudden increase in order flow can enhance the velocity of price action, thus bolstering risk exposure and creating chaotic market conditions.
- Potentially Dangerous: Negative chain reactions or "flash crashes" are often attributed to black-box trading practices. The August 2015 flash crash of the Dow Jones Industrial Average was largely blamed on momentum algorithms employed by black-box traders. The price fell 1,100 points in minutes, prompted by a flood of sell orders hitting the market instantaneously. Also, the use of dark pools in concert with algorithmic systems has given rise to concerns over investor fraud and market spoofing.
- Competitive Disadvantage: Ultra-low latency options for market access are commonly cited as creating an uneven playing field. Direct market access and server co-location are often viewed as favouring participants with sophisticated black-box capabilities.
Conversely, proponents argue that the markets and participants benefit from automated systems trading. The following points are commonly made in defense of the practice:
- Efficiency: Higher levels of market participation optimise the process of price discovery. With an abundance of traders and investors interacting with one another, ongoing trade is more likely to reflect the efficient market hypothesis.
- Liquidity: The enhanced trade volumes ensure greater market depth. Less slippage, tighter bid/ask spreads and a greater ease of market entry/exit is improved. This enables traders to engage markets more economically.
- Trader Competency: A major advantage of using black-box systems is the reduction of the human element in active trading. Through taking a hands-off approach to the markets, errors associated with human intervention are eliminated. Emotional trading and client-side latencies are reduced, while precision in execution is promoted.
As technology advances, the role that automated black-box systems play in the marketplace is likely to grow. Recent studies estimate forex volumes attributable to automated trading to be 83% of the daily handle. Large institutional investors have invested billions in the algorithmic and low-latency technologies implemented by black-boxes. For instance, one-third of the staff at financial titan Goldman Sachs are computer engineers, many of whom specialise in the automation of currency trading.
Retail traders are also joining the ranks of black-box practitioners. Pre-made systems are readily available online for purchase or lease, with many priced affordably. In addition, software trading platforms offer custom programming options for automated system development.
Regardless of the size or resources of a firm or individual, integrating a black-box trading system into operations is no longer a monumental task.
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